Bayesian Variable Selection for Nowcasting Economic Time Series
NBER Working Paper No. 19567
We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than observations. Our approach combines three Bayesian techniques: Kalman filtering, spike-and-slab regression, and model averaging. We illustrate this approach using search engine query data as predictors for consumer sentiment and gun sales.
Document Object Identifier (DOI): 10.3386/w19567
Published: Bayesian Variable Selection for Nowcasting Economic Time Series, Steven L. Scott, Hal R. Varian. in Economic Analysis of the Digital Economy, Goldfarb, Greenstein, and Tucker. 2015
Users who downloaded this paper also downloaded* these: